ALPR (Automatic License Plate Recognition) systems often function as the core module of “intelligent” transportation infrastructure applications. License plate recognition can be employed to identify a vehicle by automatically reading a license plate utilizing image-processing and character recognition technology. A license plate recognition operation can be performed by locating the license plate in an image, segmenting the characters in the plate, and performing an OCR (Optical Character Recognition) operation with respect to the characters identified. In order for OCR to achieve high accuracy, it is necessary to obtain properly segmented characters.
The license plate images captured under a realistic condition (i.e., field deployed solutions) include a number of noise sources such as, for example, heavy shadows, non-uniform illumination (e.g., from one vehicle to next, daytime versus nighttime, etc.), challenging optical geometries (e.g., tilt, shear, or projective distortions), plate frames and/or stickers partially touching characters, partial occlusion of characters (e.g., trailer hitch ball), poor contrast, and general image noise (e.g., salt and pepper noise). Additionally, variations between states in character font, width, and spacing further add difficulty with respect to proper character segmentation.
Several approaches have been implemented for performing character segmentation on license plate images. One approach involves the use of a priori knowledge such as, for example, character spacing. The presence of plates from multiple states, each having different character fonts and spacing, however, preclude the usage of such priori information. Other segmentation approaches rely only on data within the image, but assume fixed pitch character spacing. Such approaches are suitable for printing applications, but not for the ALPR systems, which can have non-uniformly spaced characters, for example, a state logo or special designation (e.g., wheelchair symbol to indicate a handicap license plate).
Based on the foregoing, it is believed that a need exists for an improved character segmentation method and system for a license plate image. The embodiment to be described in greater detail herein utilizes a two-stage approach; the first stage utilizing a vertical projection histogram, the second stage applying additional analysis such as OCR and application of state-specific rules to suspect character segments produced by the first stage.